AI that gets things done: how agentic transformation is reshaping Customer Experience

This is a guest blogpost by Richard Bassett, VP of CX Automation & AI, NiCE.

In customer service, the most valuable AI isn’t the kind that talks – it’s the kind that acts. While much recent excitement has focused on generative models that mimic human language, the next wave of transformation is being driven by systems that go beyond conversation. That’s where agentic AI comes in – technology designed to take action, solve problems, and deliver outcomes in real time.

Agentic AI is task-oriented, outcome-driven, and above all, proactive. It doesn’t just tell you what went wrong in a customer interaction – it fixes it. It doesn’t just guide an agent – it completes the task, pulls the knowledge, and triggers the workflow. This shift is already delivering measurable benefits in customer experience, operational efficiency and agent satisfaction.

From GenAI to agentic AI: moving beyond the conversation

Generative AI has opened the door to new ways of understanding and generating natural language. But agentic AI takes the next step: moving from conversation to completion. Intelligent agents now have the ability not just to assist, but to act – updating systems, issuing refunds, booking appointments or launching outbound contact when patterns suggest intervention is needed.

With platforms like ours, NiCE CXone Mpower, organisations can deploy no-code, intelligent agents that reason, trigger multi-step workflows, and integrate across front and back-office systems. These capabilities aren’t aspirational – they’re already helping reduce friction, boost satisfaction, and take pressure off human teams.

Human-centric AI that doesn’t pretend to be human

The goal of AI in CX isn’t to trick people into thinking they’re talking to a human. It’s to create experiences that feel human – responsive, personalised, and empathetic – even when handled by a system.

Agentic AI leverages context, sentiment, and memory. It knows what the customer asked last time, whether their issue was resolved, which channel they prefer, and how they felt. It uses this data to tailor tone and response, improving the journey without unnecessary escalation.

For many common tasks, automation is now matching or exceeding human performance on key metrics. Faster responses, no hold queues, and consistent service often lead to higher customer satisfaction. At the same time, human agents are freed to focus on complex or emotional cases where they add the most value.

Where GenAI adds Value: The Lloyds Banking Group example

While agentic AI focuses on autonomous action, generative AI continues to play a foundational role in augmenting human agents. Lloyds Banking Group’s recent deployment of NiCE’s GenAI technology – internally branded as Athena –  is a powerful example.

As part of its broader digital transformation, Lloyds introduced Athena to improve customer service by helping staff answer questions more quickly and effectively. Since the beginning of the year, Lloyds says approximately 21,000 of its employees have incorporated Athena into their workflows. It assists with a wide range of interactions, including personal banking, fraud and disputes, and bereavement support.

Athena equips staff with a user-friendly search tool that simplifies complex queries by using generative AI to summarise detailed articles and procedures. This significantly reduces the time needed to retrieve and understand information.

“By speeding up information retrieval and comprehension, Athena cuts the time spent on these tasks in half,” Suzanne Ellison, head of product – consumer relationships at Lloyds Banking Group said in a recent interview with Computer Weekly. “This enables our colleagues to concentrate on what truly matters – meeting our customers’ needs and providing excellent service.”

With plans to extend Athena to 43,000 end users by 2026, Lloyds is combining human expertise with GenAI-powered efficiency — streamlining service and delivering better outcomes at scale.

Shifting the role of CX leaders

The emergence of agentic AI is also elevating the role of CX leaders. As automation takes on more of the routine workload, CX leaders are being called on to shape end-to-end customer journeys, align AI investments with broader business goals, and drive cross-functional transformation.

Their influence is expanding beyond the contact centre to areas like digital strategy, data governance and innovation. Agentic AI doesn’t just change operations – it redefines leadership priorities. It’s also helping teams build confidence around AI adoption – both technically and culturally.

From reactive to proactive: rethinking inbound

One of the most significant evolutions lies in moving from inbound to proactive customer engagement. High volumes of inbound contact are increasingly being viewed as a symptom of unresolved friction elsewhere in the customer journey.

Agentic AI changes this. It can watch for triggers – like fraud or service failures – and act before the customer even picks up the phone. Instead of dealing with a complaint, it reaches out, resolves the issue, and reassures the customer. That’s not just service – it’s anticipation.

The technology to support this already exists. What many organisations now need is the infrastructure and orchestration to enable it: unified data, policy alignment, and platforms that can connect agents, systems, and workflows in real time.

Final thoughts

Agentic AI isn’t a concept on the horizon. It’s alreadychanging how CX is delivered – behind the scenes and in frontline interactions.

And as businesses scale their use of these tools, the goal remains clear: empower every agent, human or digital, to act in the moment, with the right context, for the right outcome.

Because when AI gets things done, customer experience becomes something more than efficient. It becomes effortless.